The basic model of search engines is to receive a search query from a computer user, identify search results corresponding to the subject matter or topic of the search query, and generate and return one or more web pages of search results based on the identified search results. Indeed, beyond the basic model, to improve the user experience and keep the computer user returning to the search engine, most search engines rank and sort the identified search results in an effort to present the most relevant search results to the user in the first search results page. If the desired result (or a desired result) is found on the first search results page, the user is not forced to iterate through multiple pages searching for the search result (or search results) that is desired.
Search engines use a variety of methods, techniques, and heuristics to tailor search results according to a specific computer user's interests. By tailoring the search results to the computer user's preferences the most relevant and, therefore, desirable search results are presented to the computer user in the first search results page (or at least one of the early search results pages.) One technique is to look to the computer user's social network for preferences. However, when the computer user has no specific preference and/or history with a particular topic, and if the computer user's social network similarly has no preference or history with regard to the search topic, tailoring the search results to the computer user can be challenging and often reverts to simply web page popularity.